Extensions to the Time-Oriented Database Model to Support Temporal Reasoning in Medical Expert Systems

Abstract:
Physicians faced with diagnostic and therapeutic decisions must reason about
clinical features that change over time. Electronic database-management
systems (DBMS) can increase access to patient data, but most such systems are
limited in their ability to store and retrieve complex temporal information.
For example, the skillful analysis of clinical data requires accounting for
all concurrent clinical contexts that may alter the interpretation of the raw
data. Most medical DMBSs cannot retrieve patient data indexed by a set of
specific clinical events. The Time-Oriented Databank (TOD) model, the most
widely used data model for medical database systems, simply associates a time
stamp with each observation. We describe two extensions to electronic medical
databases that were created specifically to solve temporal reasoning problems
that we encountered in constructing medical expert systems. A key feature of
both extensions is that stored data are partitioned into groupings, such as
sequential clinical visits, clinical exacerbations, or other abstract events
that have clinical relevance. The temporal network (TNET) is an object-
oriented database that extends the temporal reasoning capabilities of ONCOCIN,
a medical expert system that provides chemotherapy advice. TNET uses
persistent objects to associate intervals of time during which "an event of
clinical interest" was occurring with medical observations in a patient's
electronic medical record. TNET can capture temporal relationships among
recorded information that cannot be represented in TOD-based databases. A
second object-oriented system, called the extended temporal network (ETNET),
is both an extension and a simplification of TNET. Like TNET, ETNET uses
persistent objects to represent relevant intervals; unlike the first system,
however, ETNET contains reasoning methods (rules) that can be executed when an
event represented by an object "begins," and that are withdrawn when that
event "concludes." Although TNET and ETNET do not solve all temporal
reasoning problems found in medical decision making, these new structures
enable patient database systems to model complex temporal relationships, to
store and retrieve patient data based on clinical context, and, in ETNET, to
modify the reasoning methods available to an expert system based on the onset
or conclusion of clinical events.